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   typeofwork={博士},
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   abstract={人脸认证是当今模式识别与计算机视觉学术界和工业界的热门研究主题之一,在安防、金融、军事、交通、商务等领域均有广泛的应用前景。随着深度学习的飞速发展和数据量的日益提升,计算机的人脸识别能力在一定程度上已经超过了人类水平,目前正在向百万分之一甚至是亿分之一的误识率发展。在人脸认证模型的性能如此高的现在,如何能百尺竿头更进一步,更好地利用深度学习技术来进一步提升人脸认证模型的性能是如今的一大难题。损失函数是控制整个深度神经网络训练的中枢,本学位论文将深入探究深度学习中损失函数的机理,并把之前广泛用于通用图像识别的损失函数和多种用于度量学习的损失函数改造得更加适合人脸认证模型的训练。本学位论文的研究内容主要分为以下几点},
   databaseprovider={cnki},
}

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